Question 1

这些数据的来源是什么?

Accepted Answer

我们的数据来自于从数百万家公司收集的招聘信息。我们在公司网站、招聘平台和其他招聘平台上监控这些招聘信息。分析招聘信息提供了一种可靠的方法来了解公司正在使用的技术，包括他们使用的内部工具。

Question 2

数据多久更新一次?

Accepted Answer

我们每天更新数据，以确保您访问的是最新的可用信息。这一频繁的更新过程保证了我们的洞察力和情报反映了行业内的最新发展和趋势。

Question 3

什么是Azure Machine Learning?

Accepted Answer

Azure Machine Learning is a powerful cloudbased service provided by Microsoft as part of the Azure cloud platform It is designed to enable data scientists and developers to build train deploy and manage machine learning models more easily and efficiently With Azure Machine Learning users can leverage a range of tools and frameworks to accelerate the development of AI solutions from data preparation and model training to deployment and monitoring

Machine Learning as a Service MLaaS is the category under which Azure Machine Learning falls MLaaS platforms like Azure Machine Learning provide a set of tools and infrastructure for organizations to develop machine learning models without the need to build and maintain the underlying infrastructure This category allows businesses to harness the power of machine learning algorithms and AI technologies to derive insights improve decisionmaking processes and enhance their products and services

Azure Machine Learning was founded by Microsoft in 2014 with the aim of democratizing AI and making machine learning more accessible to a broader audience Microsofts motivation behind launching Azure Machine Learning was to empower organizations of all sizes to leverage the potential of AI and machine learning to drive innovation and accelerate digital transformation Since its inception Azure Machine Learning has gained significant traction in the market and established itself as a leading MLaaS platform

Currently Azure Machine Learning holds a substantial market share within the MLaaS category thanks to Microsofts strong presence in the cloud computing industry and its continuous investment in AI technologies With the growing demand for AIdriven solutions across various industries the market share of Azure Machine Learning is expected to continue expanding in the future As organizations increasingly prioritize AI capabilities to gain a competitive edge and improve operational efficiency Azure Machine Learning is poised to experience further growth and adoption in the market

Question 4

如何获得使用Azure Machine Learning的公司的最新列表？

Accepted Answer

您可以访问 TheirStack.com，获取使用 Azure Machine Learning 的公司更新名单。我们的平台提供了一个全面的数据库，涵盖了使用各种技术和内部工具的公司。

Question 5

Azure Machine Learning 有多少客户？

Accepted Answer

截至目前，我们拥有关于 7,071 家使用 Azure Machine Learning 的公司的数据。

Question 6

谁在使用Azure Machine Learning?

Accepted Answer

Azure Machine Learning 被广泛应用于包括 "Software Development", "Business Consulting and Services", "Broadcast Media Production and Distribution", "IT Services and IT Consulting", "IT Services and IT Consulting", "Computer and Network Security", "Financial Services", "Staffing and Recruiting", "Food and Beverage Services", "Technology, Information and Internet" 在内的各个行业的各种组织中。欲了解所有使用 Azure Machine Learning 的行业的完整列表，请访问 TheirStack.com。

Question 7

哪些公司使用Azure Machine Learning?

Accepted Answer

一些使用Azure Machine Learning的公司包括Microsoft, Accenture, PTV Planung Transport Verkehr, Avanade, Cognizant Technology Solutions, Protegrity, Navy Federal Credit Union, Nigel Frank International, PepsiCo, Dice以及更多公司。您可以在TheirStack.com上找到使用Azure Machine Learning的7,071家公司完整列表。

Question 8

哪些国家使用Azure Machine Learning最多？

Accepted Answer

根据我们的数据，Azure Machine Learning 在 美国 (2,013 companies), 英国 (484 companies), 印度 (210 companies), 德国 (184 companies), 西班牙 (167 companies), 加拿大 (165 companies), 法国 (154 companies), 荷兰 (119 companies), 澳大利亚 (82 companies), 巴西 (75 companies) 最受欢迎。然而，它被全世界的公司所使用。

Question 9

如何找到使用Azure Machine Learning的公司？

Accepted Answer

您可以在TheirStack.com上搜索Azure Machine Learning，来找到使用该技术的公司。我们跟踪数百万家公司的招聘信息，并借此发现他们正在使用的技术和内部工具。

Company	Country	Industry	Employees	Revenue
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使用 Azure Machine Learning 的公司

如何针对Azure Machine Learning用户进行定位

Azure Machine Learning 替代品和竞争对手

TensorFlow

PyTorch

scikit-learn

ML Flow

MLflow

Microsoft LUIS

ENorm

Amazon SageMaker

Stan

CUDA

Neuro

Kubeflow

Lateral

Amazon Machine Learning

Streamlit

NLTK

Perplexity

Caffe

Amazon Text to Speech

Propel

Appen

Kur

Ludwig

IBM Watson

Aquarium

Fritz

Document AI

Lamina

Apache MXNet

MXNet

Amazon Textract

Renate

Google AI Platform

Tensorflow Lite

Clipper

Igel

Bard AI

Amazon Comprehend

DeepSpeed

Weka

Microsoft Cognitive Services

Manifold

Apache Spark MLlib

Gradio

OpenVINO

Amazon Kendra

Hummingbird

GraphRAG

Run:ai

ML Kit